Documented cases of fatal and non-fatal torsade de pointes (TdP), a type of lethal ventricular arrhythmia, associated with the use of new chemical entities (NCE) have resulted in the withdrawal of a number of drugs from the market. In further response to these public health concerns, the International Council for Harmonization Guidance (ICH E14) was implemented to guide drug developers in the conduct of thorough cardiac safety assessments on all NCEs and has since virtually eliminated post-market drug withdrawals due to arrhythmia and sudden cardiac deaths. Beginning from 2005, nearly all new compounds in development have been expected to undergo rigorous testing for their potential to prolong the QT interval (a surrogate marker of proarrhythmia) on an electrocardiogram (ECG).
New drugs seeking regulatory approval typically undergo systematic evaluation of the potential to cause QT prolongation in a Thorough QT (TQT) study, in healthy subjects or as part of an intensive assessment of ECGs collected from Phase I trials using exposure response modeling. One common challenge in conducting a TQT study or in assessing QT from Phase I data is obtaining and measuring ECG data that is reliable and that is measured with good precision. Even when QT/QTc interval measurements are made by an ECG core laboratory, poor precision can occur from a number of factors, including using too few beats from an ECG recording, resulting in sampling error, or that the cardiac beats being measured are too variable and were not representative of the time point from which they are taken. The variability may be increased due to poor signal quality and/or heart rate changes, for example. When poor precision occurs in a TQT or Phase I QT study, this generally results in wider confidence intervals in the study data. In a TQT study, if the lower-bounds of the wider confidence intervals fall below pre-specified thresholds in the positive control arm of a TQT study (the positive control arm is generally derived by having study subjects take the drug moxifloxacin), then regulators would generally conclude that assay sensitivity had not been achieved in the TQT study and that the results may be deemed to be inconclusive. Similarly, if the wider confidence intervals in a TQT or Phase I QT study caused any of the upper bounds of the confidence intervals from the drug arm(s) to cross a regulatory threshold of concern (typically a 10 ms change), then such drug may be viewed by one or more regulators as requiring further study relative to its QT effect and/or that such drug may require a cardiac safety warning label related to its potential to prolong QT. Therefore, it is important in TQT studies or Phase I QT studies that methodologies and measurement techniques and technologies resulting in highly precise ECG measurements be utilized. Additionally, TQT studies are often powered in terms of the number of subjects that are put into the study based on assumptions around the level of precision that can be achieved; therefore, better precision also enables a study to either be run with fewer subjects or to minimize the likelihood of inconclusive or false positive results.
Developing methodologies and technologies that help to identify and filter out the poor quality portions of ECG recordings and the signal intervals that contain non-reliable values is valuable, because excluding this data may reduce the imprecision or otherwise improve the accuracy of the ECG interval measurements as to the current state of the subject. Additionally, another challenge in TQT and Phase I QT studies stems from the somewhat subjective nature of determining the end of a T-wave, which is used to determine a QT value. Human experts that have been highly trained in measuring ECGs have nonetheless been shown in numerous studies to be inconsistent with their fellow experts as well as to even be inconsistent with themselves over time. This is why the E14 cardiac safety guidance for conducting a TQT recommends that ECG labs conduct an “inter- and intra-reader variability” assessment as part of any TQT study so that the amount of such inconsistency and variability due to human measurement can be known. Therefore, methodologies and systems that seek to offer optimal study precision also provide a benefit by minimizing variability introduced or caused by inconsistent human measurement expertise.